Customer Stories

How A Medical Technology Company Transformed their Data Models to Improve Postoperative Outcomes

data analytics DBT interoperability life sciences snowflake

minute data pipelines, cut down from several hours historically

data efficiency gains

0 %

patients serviced with data-driven surgical outcomes per year

Empowered surgical teams and improved postoperative outcomes with data-driven insight and decision-making.

Enabled tracking of outcome-critical metrics from medical devices, including the frequency and duration of hypertension events in surgical patients

Implemented flattened reporting views in Tableau using HemoSphere telemetry and synthetic FHIR data to ensure HIPAA compliance through the development process

Challenge

The customer is an American medical technology company specializing in artificial heart valves and hemodynamic monitoring. The company has manufacturing facilities across the globe.

Encumbered by the costly and convoluted storage of medical device data in legacy systems, the client needed assistance enriching medical device data with past clinical context. They also lacked real-time reporting, data visualizations, and the kinds of extensive testing data they needed to unlock mission-critical insights.

Solution

To address the client’s need for enhanced analytics capabilities, Hakkoda architected and implemented a data stack consisting of Snowflake and dbt. This stack included a reusable and sustainable data model capable of feeding directly from intraoperative medical devices into analytics dashboards.

This powerful dbt data model enables flattened reporting views in Tableau, which leverage both ingested FHIR data and HemoSphere telemetry to provide the client team with valuable insights about patients and the interoperable devices they produce.

These dashboards can also be used by the client’s team to track important patient metrics over time, including the total number of hypotension events, average event duration, the percentage of patients with hypotensive episodes, postoperative complications by type, and compliance protocols.

The Model

Technology Used:

Snowflake

DBT

Full Time Resources:

1 Project Manager

1 Data Architect

1 Lead Data Engineer

1 Analytics Engineer

Project Duration:

10 Weeks

“The Hakkoda team was a pleasure to work with throughout our engagement. From concept to final build, we were impressed with their extensive experience and ability to deliver a great product on a compressed timeline.”

– Client Group Product Manager